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Adobe Released Puppet Recipes for Hadoop

by Michael Prokop on  Jul 01, 2010

Recently Adobe released Puppet recipes that they are using to automate Hadoop/HBase deployments to the community. InfoQ spoke with Luke Kanies, founder of PuppetLabs, to learn more about what this means.

Apache Mahout: Highly Scalable Machine Learning Algorithms

by Ryan Slobojan on  Apr 23, 2009

The Apache Mahout project, a set of highly scalable machine-learning libraries, recently announced it's first public release. InfoQ spoke with Grant Ingersoll, co-founder of Mahout and a member of the technical staff at Lucid Imagination, to learn more about this project and machine learning in general.

Amazon Rolls Out Hadoop Based MapReduce to EC2

by Scott Delap on  Apr 02, 2009

It has been possible to run Hadoop on EC2 for a while. Today Amazon simplified the process by announcing Amazon Elastic MapReduce which automatically deploys EC2 instances for computational use and includes a API for interacting with them.

Cascading - Data Processing API for Hadoop MapReduce

by R.J. Lorimer on  Oct 10, 2008

Cascading is a new processing API for data processing on Hadoop clusters, and supports building complex processing workflows using an expressive, declarative API.

Aster In-Database MapReduce

by R.J. Lorimer on  Sep 21, 2008

Aster Data Systems has announced an in-database MapReduce implementation for their nCluster database platform.

Skynet, A New Ruby MapReduce

by Sebastien Auvray on  Jan 29, 2008 4

The MapReduce design pattern to distribute data processing was introduced by Google in 2004, and came first with a C++ implementation. A new Ruby implementation is now available under the name of Skynet released by Adam Pisoni. InfoQ had the chance to catch up with Adam about its features and how it compares to an existing Ruby implementation called Starfish.

MapReduce A Step Backwards: Is Comparison to Relational Databases Fair?

by Scott Delap on  Jan 18, 2008 5

A recent article on the Database Column by David J. DeWitt and Michael Stonebraker attempts to compare the increasingly popular MapReduce programming paradigm to a relational database. The blogsphere has quickly called foul on the comparison and its reasoning.

Run Your Own Google Style Computing Cluster with Hadoop and Amazon EC2

by Scott Delap on  Nov 10, 2006 1

Amazon's EC2 Elastic Computing cloud allows developers to acquisition computing power a the rate of $0.10 per hour consumed. Work as been done to allow Hadoop an open source MapReduce implementation written in Java to run on EC2. This combination will allow developers to write scalable algorithms and then bring up large numbers of servers to use as computing power for them as needed.

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